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- Buker, P., et al.
(författare)
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DO3SE modelling of soil moisture to determine ozone flux to forest trees
- 2012
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Ingår i: Atmospheric Chemistry and Physics. - : Copernicus GmbH. - 1680-7316 .- 1680-7324. ; 12:12, s. 5537-5562
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Tidskriftsartikel (refereegranskat)abstract
- The DO3SE (Deposition of O-3 for Stomatal Exchange) model is an established tool for estimating ozone (O-3) deposition, stomatal flux and impacts to a variety of vegetation types across Europe. It has been embedded within the EMEP (European Monitoring and Evaluation Programme) photochemical model to provide a policy tool capable of relating the flux-based risk of vegetation damage to O-3 precursor emission scenarios for use in policy formulation. A key limitation of regional flux-based risk assessments has been the assumption that soil water deficits are not limiting O-3 flux due to the unavailability of evaluated methods for modelling soil water deficits and their influence on stomatal conductance (g(sto)), and subsequent O-3 flux. This paper describes the development and evaluation of a method to estimate soil moisture status and its influence on g(sto) for a variety of forest tree species. This DO3SE soil moisture module uses the Penman-Monteith energy balance method to drive water cycling through the soil-plant-atmosphere system and empirical data describing g(sto) relationships with pre-dawn leaf water status to estimate the biological control of transpiration. We trial four different methods to estimate this biological control of the transpiration stream, which vary from simple methods that relate soil water content or potential directly to g(sto), to more complex methods that incorporate hydraulic resistance and plant capacitance that control water flow through the plant system. These methods are evaluated against field data describing a variety of soil water variables, g(sto) and transpiration data for Norway spruce (Picea abies), Scots pine (Pinus sylvestris), birch (Betula pendula), aspen (Populus tremuloides), beech (Fagus sylvatica) and holm oak (Quercus ilex) collected from ten sites across Europe and North America. Modelled estimates of these variables show consistency with observed data when applying the simple empirical methods, with the timing and magnitude of soil drying events being captured well across all sites and reductions in transpiration with the onset of drought being predicted with reasonable accuracy. The more complex methods, which incorporate hydraulic resistance and plant capacitance, perform less well, with predicted drying cycles consistently underestimating the rate and magnitude of water loss from the soil. A sensitivity analysis showed that model performance was strongly dependent upon the local parameterisation of key model drivers such as the maximum g(sto), soil texture, root depth and leaf area index. The results suggest that the simple modelling methods that relate g(sto) directly to soil water content and potential provide adequate estimates of soil moisture and influence on g(sto) such that they are suitable to be used to assess the potential risk posed by O-3 to forest trees across Europe.
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| 2. |
- Turro, Ernest, et al.
(författare)
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Whole-genome sequencing of patients with rare diseases in a national health system.
- 2020
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 583:7814, s. 96-102
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Tidskriftsartikel (refereegranskat)abstract
- Most patients with rare diseases do not receive a molecular diagnosis and the aetiological variants and causative genes for more than half such disorders remain to be discovered1. Here we used whole-genome sequencing (WGS) in a national health system to streamline diagnosis and to discover unknown aetiological variants in the coding and non-coding regions of the genome. We generated WGS data for 13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to 1,138 of the 7,065extensively phenotypedparticipants. We identified 95 Mendelian associations between genes and rare diseases, of which 11 have been discovered since 2015 and at least 79 are confirmed to be aetiological. By generating WGS data ofUK Biobankparticipants2, we found that rare alleles can explain the presence of some individuals in the tails of a quantitative trait for red blood cells. Finally, we identified four novel non-coding variants that cause disease through the disruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates a synergy by using WGS for diagnosis and aetiological discovery in routine healthcare.
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